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1 City Research Online City, University of London Institutional Repository Citation: Battaglia, F. & Gallo, A. (2017). Strong boards, ownership concentration and EU banks' systemic risk-taking: Evidence from the financial crisis. Journal of International Financial Markets, Institutions and Money, 46, pp doi: /j.intfin This is the accepted version of the paper. This version of the publication may differ from the final published version. Permanent repository link: Link to published version: Copyright and reuse: City Research Online aims to make research outputs of City, University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to. City Research Online: publications@city.ac.uk

2 Strong boards, Ownership concentration and EU banks systemic risk-taking: evidence from the financial crisis FRANCESCA BATTAGLIA Assistant Professor, Dipartimento di Studi Aziendali e Quantitativi, Università degli Studi di Napoli "Parthenope", Via G. Parisi, n. 13, Napoli Italy, , francesca.battaglia@uniparthenope.it ANGELA GALLO Assistant Professor, Dipartimento DISA-MIS, Università degli Studi di Salerno, Via Ponte don Melillo Fisciano (SA), Italy, angallo@unisa.it Abstract We examine the effects of board composition and ownership on traditional measures of bank risk and proxies of bank tail and systemic risk. Both banks corporate governance shortcomings and systemic risk-taking have been recognized among the potential causes of the 2007 financial crisis. Yet, their interaction has received less attention so far. Based on a sample of 40 European banks over the period , we find that the boards characteristics affect banks systemic risk, except for board independence and that this relation depends on capital regulations, banking systems ownership structures and bank activity restrictions. Keywords: board composition; bank ownership; systemic risk; financial crisis JEL classification: G01; G21; G32 1. Introduction Corresponding author

3 The role of corporate governance in banking has been highlighted by academics as well as by regulators and policy makers (see e.g. Basle Committee on Banking Supervision, 2010; Organization for Economic Co-operation and Development, 2010). Many academic studies emphasize how flaws in bank governance played a key role in the performance of banks during the crisis (Diamond and Rajan, 2009; Bebchuk and Spamann, 2010, Beltratti and Stulz, 2012). Since the 2007, an increasing number of proposals and initiatives have attempted to identify and mitigate these flaws revealed by the financial crisis (Kirkpatrick, 2009) aiming to promote better corporate governance standards in banking, while recognizing the special nature of banks when compared to other firms. On the other hand, the financial crisis revealed the dramatic impact of excessive risktaking behaviour of banks on the global financial stability, especially in terms of underestimated consequences of unregulated systemic risk-taking. As the literature has widely investigated poor or weak corporate governance as well as the increasing systemic nature of the banking sector as major causes of the crisis, to the best of our knowledge there is still a limited understanding of the relationship between corporate governance characteristics and banks incentive to become more expose to systemic risk. As suggested by de Andres and Vallelado (2008), the aim of banking regulators to reduce the runs and their systemic consequences on the stability of the system might come into conflict with the main purpose of shareholders which is to improve the shareholders value by also increasing risk-taking. Taking on risks and tail and systemic risks, in particular, may enhance bank performance in the short run (i.e. by increasing the leverage), but it can cause significant damage to the institution and the whole system when such risks materialize (i.e. fire sales effects ). During the global financial crisis, European banks exposed themselves to tail and systemic risks in various ways. Among others, the most recent literature has highlighted how European banks' exposures to tail risks in the form of shadow banking activities were later transformed into severe losses on the balance sheets (Acharya et al., 2013: Arteta et al., 2013).

4 An increase in systemic and tail risks by large banks could be supported by the implicit too-big-to fail guarantee and the reduced market discipline (Acharya et al.,2010). In fact, it could be difficult, both for outsiders and insiders, to distinguish between risk-taking activities that generate high returns and those that offer high returns as compensation for taking tail risk through complex and opaque activities (Ellul and Yerramilli, 2013). In this context, the presence of a strong and independent board of directors may be crucial for the control of tail and systemic risks exposures and could explain the cross-sectional differences across banks in terms of tail and systemic risks. In other words, to the extent that the board plays its own role, we would expect banks with strong boards to be perceived as less risky and then to performed better during the crisis, when the tail risk occurs. Among several corporate governance characteristics, the Basel Committee on Banking Supervision (2006) in its consultative document "Enhancing Corporate Governance of Banking Industry, places the board of directors as an essential part of the bank regulatory reforms. In addition, the Basel Committee emphasizes the role of the board of directors in the implementation of pillar II and, more generally, for whole risk management architecture (Basel Committee on Banking Supervision, 2005, pp ). This role is important for banks more than for other firms, because of i) the director s fiduciary responsibilities which are extended beyond shareholders to include a wider range of stakeholders, i.e. depositors and regulators (Macey and O Hara, 2003); ii) the complexity of the banking business: the presence of opaque bank lending activities reduces the ability of shareholders and debt holders to impose effective governance (Levine, 2004); iii) the limited competition, intense regulation and the higher informational asymmetries (de Andres and Vallelado, 2008). Because the board is a key mechanism to monitor managers behaviour and to advise them on strategy identification and implementation, the directors specific knowledge of the complexity of the banking business is crucial to perform these roles efficiently. Pathan (2009) defines a strong board (i.e., small board and more independent directors) as a board that is more effective in monitoring bank managers and that reflects more the bank shareholders interests. He finds that banks with strong governance attributes may take more risk. Although some studies

5 document a positive association between board size and bank risk behaviour during the financial crisis period (Fortin, 2010; Minton et al., 2010; Adams, 2012; Peni and Vahamaa, 2012), other authors argue that the risk of financial firms vary inversely with the strength of corporate governance (Akhigbe and Martin, 2008; Beltratti and Stulz, 2012; Wang and Hsu, 2013; Faleye and Krishnan, 2015). Erkens et al. (2012) and Berger et al. (2014) find no support for the proposition that board size is related to bank performance, both in terms of profitability and risk during the crisis. Also the growing stream of literature supporting the importance of non-independent directors for corporate boards show mixed results (Adams and Ferreira, 2007; Baranchuck and Dybvig, 2009). The post-crisis literature does not provide much support that board independence is positively related to performance, in terms of risk and profitability (Cornett et al., 2010; Yeh et al., 2011). Both Minton et al. (2010) and Fernandes and Fich (2016) find a not significant relationship between board independence and firm performance, while the empirical results of Aebi et al. (2012), Beltratti and Stulz (2012), Erkens et al. (2012) and Wang and Hsu (2013) show that the presence of independent directors in negatively related to the risk behavior of financial institutions. Since ownership structures may affect bank performance, both in terms of profitability and risk, a recent stream of research on bank risk-taking typically incorporates information on each bank s ownership structure. Also referring to that topic, the pre and post-crisis literature shows mixed results without offering a conclusive view (Gropp and Kohler, 2010; Beltratti and Stulz, 2012; Ellul and Yerramilli, 2012; Erkens et al., 2012; Berger et al., 2014). This heterogeneity of findings suggests that results may vary with the ownership structure under investigation (i.e. insider ownership, institutional ownership, bank ownership, ownership by lower management, ownership by chief officers and outside directors, etc.). In our research we choose to rely on the works by Laeven and Levine (2009) and Beltratti and Stulz (2012). Laeven and Levine (2012) find that banks with concentrated ownership are riskier than banks with dispersed ownership. Moreover, they suggest that the bank ownership structure strongly affects the relation between bank risk and regulation: while stricter regulation decreases the risk of a bank with dispersed ownership, it

6 increases the risk of a bank with a large controlling shareholder. Therefore, also in line with Beltratti and Stulz (2012), we estimate the ownership of controlling shareholders and control for the effect of bank regulation. To the best of our knowledge, our paper is one of the first studies to analyse the European banks ownership structure, by using a new dataset provided by Garcia-Kuhner et al. (2013). By using data on 40 large publicly traded European banks, we examine whether and how banks with strong boards and different ownership concentrations are associated with higher systemic and tail risks. Academics and regulators have developed different concepts and proposals in order to assess systemic risk. We choose the measures of risk developed by Acharya et al. (2010), defined as the Marginal Expected Shortfall (MES). Together with the (quasi-) market Leverage ratio (LEV), the MES is the main determinant of the Systemic Expected Shortfall (SES). Next to the MES, we employ the Expected Shortfall (ES) and two traditional measures of risk: the Volatility (VOL), estimated as the annualized daily standard deviation of the stock returns, and the Z-score, that is the distance to default (the higher the Z-score, the lower the probability of default of the bank and thus the risk of a bank failure). Since the summer of 2007, the financial system has faced two severe systemic crises and European banks have been at the centre of both (Acharya and Steffen, 2012). To avoid a confusing effect of the latter crisis, defined as the sovereign crisis, which origins and implications are different from the the former, we decide to focus only on the period of financial turmoil from 2007 to Moreover, since the previous literature suggests that the bank performance during the crisis is related to the risk behaviour before the crisis, we decide to include in our analysis also the year We focus on three corporate governance dimensions related to the board composition and functioning: (1) the board size, (2) the board independence, and (3) the frequency of the board meeting per year, measured as of December We also analyse the ownership concentration by considering the largest shareholder s percentage ownership of the cash flow rights attributable to a bank s total equity. Given that the prior literature (see e.g. Black et al.

7 2006; Cremers and Ferrell, 2010) suggests that the corporate governance structures change slowly, following Erkens et al. (2012), we use data for year 2006, prior to the onset of the crisis. Hence, we assume that the strength of governance mechanism incorporated in the year 2006 is reflected in bank risk-taking during the period We find that banks with larger board size and lower number of board meetings per year experience more severe losses than other banks during the crisis, but also that they contribute strongly to the losses of the banking system as a whole, i.e. to the spread of a systemic crisis. On the other hand, the number of independent directors is relevant for our proxy of the probability of bank insolvency. Moreover, we find that differences in banking regulations and ownership across countries are generally correlated with systemic risk taking. In particular, banks headquartered in European countries with i) more restrictions on bank activities, ii) less restriction on capital and iii) more concentrated banking system took more systemic risk during the crisis. As it is common in studies of corporate governance, endogeneity could bias our results. We take a number of steps to control for it. First, in all our models we control for bank-specific characteristics that are likely to affect risk-taking decisions, such as size, leverage, gross loans, impaired loans, tier 1 and liquid assets (besides year and country dummies). Moreover, our corporate governance proxies are taken at the year preceding our investigated period. To control for the possibility of omitted variable bias we exploit the insight from Altonji et al.(2005), as in Chalermchatvichien et al. (2014), and find that the endogeneity bias is more unlikely in our results. We contribute to the existing literature in several respects. First, the investigated period allows us to shed a light on the relationship between corporate governance and banks risk exposures during persistent years of financial distress. Second, with respect to previous and more recent studies on the topic, mainly focusing on the U.S. banks, we are the first who provide insights into European markets. Thirdly, as far as it could be ascertained, this is the first study to employ market-based

8 systemic and tail risk measures referring to the board effectiveness in monitoring bank managers (i.e. board size, board independence, number of meetings) in a single research, including ownership concentration. This is notably relevant given that the turmoil has illustrated how excessive risktaking could lead to financial instability by contributing to an increase in the occurrence of banking crises. The remainder of the paper is organized as follows. In Section 2, we analyse the relevant literature on corporate governance and systemic risk to develop our testable hypotheses. In Section 3, we describe the estimation framework, our sample and the model variables. In Section 4, we present and discuss the empirical analysis and its results. In Section 5, we describe the robustness tests and Section 6 concludes. 2. Related literature and empirical hypotheses 2.1 Corporate governance and bank risk-taking during the financial crisis Previously, an extensive empirical literature has documented that banks with strong corporate governance mechanism are generally associated with better financial performance, higher firm valuation and higher stock returns (Caprio et al., 2007; Cornett et al., 2009; de Andres and Vallelado, 2008; Hanazaki and Horiuchi 2003; Jirapron and Chintrakarn, 2009; Laeven and Levine, 2009; Macey and O'Hara, 2003; Mishra and Nielsen, 2000; Pacini et al., 2005; Sierra et al., 2006; Webb Cooper, 2009). Yet, the existing literature has only partially investigated the relationship between governance and bank risk-taking, since several studies analyse a specific type of risk and governance dimensions, usually focusing on the United States. More recently, empirical papers look at the above-mentioned relationship over periods of financial turmoil, by focusing on the board characteristics (i.e. size, board independence, CEO-chairman duality, financial expertise of directors), the risk management and culture (i.e. existence of board risk committee, presence of the CRO on board, the professional background of the CEO) and the ownership structure. Although

9 their evidence is not conclusive, their results provide empirical evidences of the following: larger and more diverse boards have sometimes been associated with more risk; the number of the independent directors does not affect risk-taking and, moreover, the results on board financial expertise are mixed; stronger risk management functions and culture are related to less risk; empirical results on the relationship between performance-linked remuneration in the form of options and risk are mixed, even if this kind of compensation tend to be associated with more risk; several studies show a positive association between institutional or insider ownership and bank risktaking referring to the financial crisis, but the evidence is not conclusive for other periods. Before moving on the analysis of the various studies, it is worth to notice that only few researches analyze the influence of governance on bank tail and systemic risks during the credit crisis. In particular, we refer to the works by Adams and Ragunathan (2013) and Ellul and Yerramilli (2013). Moreover, we point out that none of these studies focuses on the relationship between the boards effectiveness in monitoring bank managers (i.e. board size, board independence, number of meetings) and ownership concentration, on one hand, and bank tail and systemic risk, on the other hand. For the purposes of our research, our literature review will focus on the analysis on the most recent and relevant studies, investigating the relationship between both board characteristics and ownership concentration, on one hand, and bank risk-taking, on the other hand, over the financial crisis period. Referring to the board size, the sample investigated by Adams (2012) compares US banks that were bailed out during the credit crisis with those that were not showing that financial institutions that received TARP support in either 2008 or beginning of 2009 had larger boards than those that did not. By analyzing a sample of US publicly-traded banks with total assets greater than $ 1 billion, Minton et al. (2010) report similar findings, as larger boards are associated with increases in the likelihood of receiving TARP funds. The authors argue that their results on TARP support can be

10 interpreted differently: on the one hand, receiving TARP money may reflect poor performance, but, on the other hand, TARP funds could also be viewed as a unique opportunity for banks to raise relatively cheap funds during the crisis. If riskier banks were the ones that were bailed out, this implies that financial institutions with larger boards took more risk. However, we specify that these results are not consistent with those reported by Minton et al. (2010) for their non-crisis period, as they find that bank board size is negatively related to risk-taking. Using a sample of large U.S. bank holding companies in the financial crisis period, Fortin et al. (2010) suggest that banks characterized by strong governance mechanisms may take more risk. These results are in line with those of Pathan (2009), who, by analysing a sample composed of 212 large US bank holding companies during the pre-crisis period ( ), finds that a small bank board is associated with more bank risk, proxied by several risk measures (total risk, idiosyncratic risk, systematic risk, assets return risk, Z-score) whereas a high number of independent directors seem to imply less risk exposure by banks. Peni and Vahamaa (2012) find a positive and significant relationship during the 2008 financial crisis for large publicly traded US banks. In particular, they show that banks with stronger corporate governance (small boards and more independent directors) mechanisms have higher profitability, higher market valuations and less negative stock returns amidst the crisis. Several papers show a negative impact of the board size on bank risk. Akhigbe and Martin (2008) argue that corporate governance is inversely related to bank risk behavior. Beltratti and Stulz (2012) focus on banks in 31 countries and document that large banks with lower leverage ratios have less negative stock returns during the crisis, but also that banks with strong boards perform worse over the period from July 2007 to December 2008 than other banks. Wang and Hsu (2013) investigate the relationship between board composition and operational risk events of 68 U.S. financial institutions in the period from 1996 to Their findings suggest that board size is negatively and non-linearly associated with the possibility of operational risk events. Faleye and Krishnan (2015) employ three measures of bank risk-taking in lending decisions, namely the borrower s long-term S&P credit rating, the inclusion of financial covenants in loan contracts and the bank s decision to

11 diversify its lending risk through syndication. Their sample includes 340 bank-years for 80 banks over They find that banks with smaller boards provide fewer junk loans and are less likely to underwrite speculative loans. The inclusion of financial covenants is not related to board size. Unlike the results of the previous studies, both Erkens et al. (2012) and Berger et al.(2014) find no support for the proposition that board size is related to bank performance, in terms of profitability and risk during the crisis. In particular, by investigating a dataset composed of 296 large financial firms, including non-banks, across 30 countries during the turmoil, Erkens et al. show that the relationship between the board size (i.e. number of directors) and their measure of bank risk behavior, proxied by the expected default frequency and the standard deviation of weekly banks stock returns, is not significant. Likewise, Berger et al.(2014) argue that management structures of US commercial banks, including board size, are not decisive for banks stability (i.e., propensity to default) during the recent financial crisis. In particular, by focusing on a sample composed of 85 default and 256 no default US commercial banks, they show that the board size is not related to the probability of default of the financial intermediaries. As we have mentioned before, the post-crisis literature does not provide much support that board independence is positively related to performance. Both Minton et al. (2010) and Fernandes and Fich (2016) find a not significant relationship between board independence and firm performance, while the empirical results of Aebi et al. (2012), Erkens et al. (2012) and Wang and Hsu (2013) show that the presence of independent directors is negatively related to their banks performance measures. Consistently with the evidence provided by Beltratti and Stulz (2012), who find a negative correlation between board independence and risk-taking, also Erkens et al. (2012) show that firms with more independent boards experience worse stock returns during the crisis, by arguing that this is not caused by higher risk-taking, as board independence is not related to the expected default frequency and stock return volatility. One exception is the study of Cornett et al.

12 (2010), that explores the relation between several corporate governance mechanisms and bank performance, by analyzing a sample composed of all US publicly-traded bank holding companies, that operate at any time during the 2003 through 2008 period. The authors find that a more independent board is positively related to banks performance during the crisis period, while the governance variable is not significant before the credit crisis. As highlighted by the empirical findings of Beltratti and Stulz (2012) and Erkens et al. (2012), the post-crisis research show some evidence that board independence is negatively related to risk-taking. Similar results are reported by Minton et al. (2010). Likewise, Faleye and Krishnan (2015) find that board independence reduces the bank s riskiness measured as the borrower s long-term S&P credit rating and the inclusion of financial covenants in loan contracts, but it is not related to the bank s decision to diversify its lending risk through syndication. Finally, Yeh et al. (2011) investigate if the performance during the recent financial crisis is better for financial institutions with more independent directors who sit on board committees. By analyzing data on financial institutions from the G8 countries, their results suggest that independence in auditing and risk committees is positively related to the crisis performance. This effect is particularly significant for civil law countries, which are characterized by poor shareholder protection practices. In addition, these authors find that the positive relationship between committee independence and banks performance is more relevant for those financial institutions having more excessive risk-taking behaviors. Since ownership structures may affect bank performance, both in terms of profitability and risk, many post-crisis studies focus on the analysis of this relationship. As outlined by the IMF (2014), in general, institutional ownership is related to less risk-taking, while insider ownership is associated with more risk. However, the IMF study (2014) states that the presence of institutional investors and of large insider ownership correlates with more risk in The underlying idea is that banks with higher percentage of insider or institutional investors hold a higher fraction of the ownership of the company and reduce their risk exposure, since they have a lot to lose. On the other hand, when

13 the firm is close to default (as many did in 2008), managers take on more risk, as they have less to lose. Referring to that topic, the post-crisis studies show conflicting results. By analysing an international sample of banks, Beltratti and Stulz (2012) find that ownership by large shareholder is not associated with better performance during the 2007 crisis; however, their evidence shows a positive relationship between manager ownership and the stock performance referring to the same period. The results of Berger et al. (2014) suggest that defaults are strongly influenced by a bank s ownership structure: high shareholdings of lower-level management, such as vice presidents, increase default risk significantly. In contrast, shareholdings of outside directors and chief officers (managers with a chief officer position, such as the CEO, CFO, etc.) do not have a direct impact on the probability of failure. By analyzing a sample including banks from 25 OECD countries over the period , Gropp and Kohler (2010) report that savings banks suffered larger losses during the crisis than cooperative or mutual banks. Moreover, they find that aligning the interests of managers and shareholders increases banks risk-taking, measured by the deviation of long term average ROE. In contrast to these findings, Ellul and Yerramilli (2012) show that banks with higher institutional ownership take less risk as measured by their Risk Management Index (RMI). However, in the presence of deposit insurance, they document the effect reverses and a positive correlation between tail risk and institutional ownership. Erkens et al. (2012) report that financial institutions with more independent boards and higher institutional ownership experience worse stock returns during the crisis period. 2.2 Testable Hypotheses Based on the prior literature, we focus on the relationship between risk-taking and the following characteristics of the board of directors: the board size, the percentage of independent directors and the frequency of board meetings per year. The board of directors is an economic institution that, in theory, helps to solve the agency problems inherent in managing an organization (Hermalin and

14 Weisbach, 2003). Hence, the role of the board of directors in the banking industry is to monitor and advise managers. Larger boards of directors could better supervise managers and bring more human capital to advise them. However, boards with too many members may suffer from problems of coordination, control, and flexibility in the decision-making process. Large boards also give excessive control to the CEO, harming efficiency (Yermack, 1996; Eisenberg et al., 1998; Fernández et al., 1997). Therefore, the trade-off between advantages (monitoring and advising) and disadvantages (coordination, control and decision-making problems) has to be taken into account. Given the time horizon we investigate, which is characterized by financial instability, we expect coordination and control functions to gain considerable importance compared to monitoring and advising and thus that small boards are associated with less risk-taking. In particular, we expect this idea to be confirmed by our measures of tail and systemic risks, which refer to extreme conditions of the individual banks and of the market, respectively, whereas the flexibility in decision-making is even more valuable. To summarize, the formal specification of our first hypothesis is the following: Hypothesis 1 (H 1 ): Tail and systemic bank risk-taking are positively related to board size. As we have previously argued, the post-crisis corporate governance literature offers no conclusive evidence on the effect of independent directors on bank risk-taking. Moreover, also the extensive pre-crisis literature on the topic provide mixed results. Independent directors are believed to be better monitors of managers as independent directors value maintaining reputation in directorship market but the findings in this instance are mixed (Fama and Jensen, 1983; Bhagat and Black, 2002). According to Pathan (2009), when the monitoring function is prevalent, we expect a positive link between the presence of independent and bank risk-taking. Moreover, Hermalin and Weisbach (2003) point out that the board independence is not important on a day to day basis and propose that board independence should only matter for certain board actions, particularly those that occur infrequently or only in a crisis situation (Hermalin and Weisbach 2003, p. 17). However, an excessive proportion of outside directors could damage the advisory role of boards, since it might

15 prevent bank executives from joining the board. Inside directors are able to provide the board with valuable information that outside directors would find difficult to gather. In other words, insider directors facilitate the transfer of information between board directors and managers (Adams and Ferreira, 2007; Harris and Raviv, 2008; Coles et al., 2008). We assume that a board with more inside directors is perceived as abler to support the managers in the difficult decision-making process needed in extreme market conditions. Thus, the formal specification of our second hypothesis is as follows: Hypothesis 2 (H 2 ): Tail and systemic bank risk-taking are negatively related to the number of independent directors. We investigate the effect of the frequency of board meeting per year, as a proxy of the better functioning of the board (Vafeas, 1999). It is worth to notice that while in the pre-crisis literature several researches deal with this corporate governance dimension, there are no empirical studies analyzing the relationship between the number of the board meetings and the banks risk during the financial crisis period. As mentioned by de Andres and Vallelado (2008), meetings provide board members with the chance to come together, to discuss and exchange ideas on how they wish to monitor managers and bank strategy. Hence, the more frequent the meetings, the closer the control over managers and the more relevant the advisory role of the board. Furthermore, the complexity of the banking business and the importance of information (as for the insider directors) both increase the relevance of the board advisory role. By contrast, frequent meetings might also be a result of the board reactions to poor performance. Once again, given our focus on the effect of corporate governance on extreme market conditions, we expect that a higher number of meetings to be perceived as a proxy of a more timely response of the board to the external conditions and thus to be associated with a lower level of tail and systemic risks.

16 Hypothesis 3 (H 3 ): Tail and systemic bank risk-taking are negatively related to the number of meetings of the board of directors. Finally, we turn to analyse the ownership structure effect on bank risk-taking. The empirical evidence of our literature review show conflicting results. Moreover, also referring to this corporate governance dimension, the extensive pre-crisis literature provide mixed results. Laeven and Levine (2009) find that more powerful owners with substantial cash flows have the power and incentives to induce bank s managers to increase risk-taking, in line with the agency theory. The idea is that when a bank has a concentrated share ownership, the tendency of managers (with bank-specific human capital and private benefits of control) to engage in less risky activities may be capped by shareholders (the resulting prediction is a positive relation between ownership concentration and bank risk). Beltratti and Stulz (2012) find that greater shareholder influence through board of directors was not associated with better performance in the period after the 2007 crisis. Contrary to the agency theory, Li and Song (2010) find a negative relation between concentrated ownership and bank insolvency risk. This evidence is consistent with Burkart et al. (1997), who suggest that the monitoring effect exerted by the large shareholders deprives the managers of their private benefits, thereby reducing managerial initiatives. By assuming that more powerful owners of large banks can exploit greater bargaining power with regulators and governments in the event of a financial distress, we would expect concentrated ownership to be associated with higher systemic and tail risks than banks with dispersed ownership. However, large shareholders can also impose a better monitoring on managers and, more in general, obtain a better insight into the complex and opaque activities, which lead to bear tail and systemic risk. Thus, the formal specification of our fourth hypothesis is as follows: Hypothesis 4 (H 4 ): Tail and systemic bank risk-taking are negatively related to ownership concentration.

17 2.3 Systemic risk measures The literature on systemic risk is recent and can be broadly separate into those taking a structural approach, using contingent claims analysis of the financial institutions assets (Lehar, 2005; Gray et al, 2009; Gray and Jobst, 2009), and those taking a reduced-form approach based on the statistical tail behaviour of institutions asset returns. In particular, referring to the latter strand of the literature, Brunnermeier et al. (2009) claim that a systemic risk measure should identify the risk to the system posed by individually systemic institutions, which are so interconnected and large that they can cause negative risk spillover effects on others, as well as by institutions that are systemic as part of a herd. Adrian and Brunnermeier (2008) refers to the financial sector's Value at Risk (VaR) of a bank as a given VaR loss (CoVaR) by using quantile regressions on asset returns computed by using data on market equity and book value of the debt. Hartmann et al. (2005) use multivariate extreme value theory to estimate the systemic risk in the US and European banking systems. Similarly, De Jonghe (2010) presents estimates of tail betas as a systemic risk measure for a sample of European financial firms. Goodhart and Segoviano (2009) look at how individual firms contribute to the potential distress of the system by using the CDSs of these firms within a multivariate copula setting. Our research will focus on the systemic risk measure referred to as Marginal Expected Shortfall, proposed by (Acharya et al. 2010). In comparison with other measures of firm-level risk, the MES is the only systemic risk measure based on market data, specifically accounting for extreme events in the left tail. MES has shown a higher predictive power in detecting a bank s contribution to a crisis (Acharya et al. 2010). MES can be defined as the expected equity loss per dollar invested in a particular bank if the overall market declines by a certain amount and it is computed as the average return of each bank during the 5% worst days of the market. We first note that MES has been originally proposed by Tasche (2000) and later used by Yamai and Yoshida (2002). One example of this approach is provided in Engle and Brownlees (2010). They show that the banks with the

18 highest MES are the banks that contribute the most to the market decline. Therefore, those banks are the most notable candidates to be systemically risky. Equity holders in a bank that is systemically risky will suffer major losses during a financial crisis and, consequently, will reduce positions if a crisis becomes more likely. MES measures this effect and it clearly relies on investors recognizing which bank will do badly in a crisis. 3. Sample, variables and econometric models In this section, first we describe our sample and the selection strategy we adopt in order to build up it, then we describe and analyse the variables (dependent variables, key independent variables and control variables) of the models we implement. Finally, we focus on the explanation of the estimation framework. 3.1 Sample and selection strategy Our initial sample consists of the largest publicly listed active commercial banks, bank holdings and holding companies headquartered in the European Union over the period This time period includes the financial crisis but allows us to avoid data inconsistency related to the introduction to Basle II in 2005 and the broke out of the sovereign debt crisis in The empirical analysis requires data on the banks corporate governance structures, banks and holdings financial information and stock prices, regulatory and macroeconomic information at country-level. In detail, information on bank board structures are hand-collected from the annual reports, the financial information and the data on stock prices and market capitalizations of banks are mostly obtained from Bankscope and from Bloomberg database, respectively. Regulatory and macroeconomic variables are from Caprio et al. (2007) using data in 2007 database (revised in June 2008) downloaded from the World Bank database.

19 After eliminating the banks with limited market price, financial and/or board-level information, we obtain a sample comprising 40 individual banks and holdings companies and 200 firm-year observations for the fiscal years In particular, we adopt the following criteria to build up our sample. First, we restrict our sample to commercial banks, bank holdings and holding companies that were publicly traded for the overall analysed period (i.e ) in the European Union. This results in 123 financial firms. Then, we consider only firms with a market capitalization at the end of 2006 greater than EUR 1 million. This because large financial institutions were at the centre of public attention during the financial crisis and, more importantly, the size in terms of total assets is identified as one of the main factors to assess the systemic relevance of a financial institution. This additional limitation reduces our sample to 52 units. Third, we lose 12 firms because they lack of corporate governance information at the end of 2006 (prior to the onset of the crisis). Data on the ownership concentration of European banks is not readily available in Bankscope, where only current ownership information is reported, but it is not provided on an historical basis. Moreover, the computation of the ultimate shareholders implies the use of other databases because a large portion of European banks is owned by non-financial companies. Garcia-Kuhner et al. (2013) build a database on ownership of European banks. They use the entire universe of Bankscope (DVDs) and Amadeus Top 250,000 to track the ultimate shareholders of European banks. Before tracing back the ultimate shareholders of each bank, they cleaned the database from all those entries where the shareholders are recorded with a generic name ( Institutions, Management, Private shareholders ) for which they cannot identify a specific individual/ company as a shareholder 1. When they find that a bank is owned by another company (either financial or non-financial), they identify the owners of that company and so on until they cannot trace back any further. Contrarily to 1 This is the case for one of the banks in our dataset, i.e. National Bank of Greece SA. The only entry available for this bank is recorded as "Autocontrole", a generic name. Nonetheless, for this bank, they retrieved from an old file the generic name of the shareholder and the corresponding ownership and have included it in the file they sent to us.

20 Laeven and Levine (2009) they do not impose any threshold (they impose a threshold of 10% in each link along the ultimate control chain). So they retrieve the ultimate shareholders of each bank at any level of ownership. Once they have identified all ultimate shareholders, for each of them they compute the cash flow rights and voting rights. Following Laeven and Levine (2009) we include the data on cash flow rights in our analysis. Despite the small number of individual banks, the amount of total assets of our sample totalled about 15,565,731 million at the end of 2006, this because it covers a substantial proportion of the total amount of banking assets in the European Union by construction. 3.2 Variables Key independent variables: board variables and ownership Our key independent variables are the governance variables relating to the definition of strong board and ownership. Following Pathan (2009), the effectiveness of the board of directors in monitoring and advising managers determines its power and we use the term "strong board" to indicate a board more representing firm shareholder interest. Thus, a strong bank board is expected to better monitor bank managers for shareholders. Our proxies of strong boards are a small board size, a high percentage of independent directors in the board and a high frequency of board meetings. In detail, we define board size (BS) as the number of directors on the board. Independent directors (IND) is measured as the percentage of independent directors in the board. An independent director has only business relationship with the bank and his or her directorship, i.e. an independent director is not an existing or former employee of the banks or its immediate family members and does not have any significant business ties with the bank. The frequency of the board meetings (BM) is measured as the median of the number of the meetings held the in the years 2004, 2005, 2006 (before the crisis). This variable takes into account the internal functioning of the board (de Andres and Vallelado, 2008) and how the board operates. Since meetings provide board

21 members with the chance to come together and discuss on how they wish to monitor managers, we can argue that more frequent meetings imply closer control over managers. As to our proxy of ownership concentration (CFR), following Leavin and Levine (2009), we construct a dummy variable that assumes a value equal to 0 if the cash-flow rights of the largest ultimate shareholder are less than 10% (the bank is widely-held). Dependent variables: bank risk measures We use multiple proxies of bank risk to show whether strong boards have any impact on the bank risk-taking. In particular, our four measures of bank risk-taking include Marginal Expected Shortfall (MES), Expected Shortfall (ES), the Volatility (VOL) and the Z-score. All these measures are based on market data but the Z-score. To allow for comparison with previous studies (see Beltratti and Stulz, 2012; Erkens, 2012), we include the risk measure Volatility (VOL) based on banks market returns over the period Following Peni and Vahamaa (2011), bank VOL is calculated as the annualized standard deviation of its daily stock returns (R it ) for each fiscal year. The daily stock return is calculated as the natural logarithmic of the ratio of equity return series, i.e. R it = ln (P it /P it-1 ), where the stock prices are adjusted for any capital adjustment, including dividend and stock splits. VOL captures the overall variability in bank stock returns and reflects the market s perceptions about the risks inherent in the bank s assets, liabilities, and off-balance-sheet positions. Both regulators and bank managers frequently monitor this total risk measure. Another traditional measure of bank risk used in the literature is the Z-score (e.g., Laeven and Levine 2009), defined as the distance to default, which equals the average of the return on assets (ROA) plus the equity-asset ratio divided by the volatility of ROA. For cross-sectional analysis, the equity asset ratio, average and the volatility of ROA are computed for each bank over the entire

22 sample period ( ) (Garcia-Kuhnert et al. 2013). It indicates the number of standard deviations that ROA would need to fall in order to exhaust equity and force a bank failure. The distance to default (DD) is closely linked to the probability of default (PD) so that the higher the distance to default, the lower the PD and thus the risk of a bank failure. As Leaven and Levine (2009), we take the natural logarithm of the Z-score, which is normally distributed, to smooth the effect of extreme values. In order to measure a bank exposure to tail risk, we use the Expected Shortfall (ES). ES is coherent and more robust than Value at Risk (VaR) as largely investigated by the literature on the topic. Moreover, since we investigate the effect of governance structure on risk-taking decisions of banks during the crisis, we want to focus on the tails of the distribution whereas VaR only measures the distribution quantile and disregards extreme loss beyond the VaR level. This means that it fails to take into account the risk referred to as tail risk. To alleviate the problems inherent in VaR, Artzner et al (1999) propose the use of Expected Shortfall. Starting from the same measure, the Expected Shortfall, but computing it for the overall banking system, Acharya et al. (2010) and Brownlees et Engle (2010) derive the Marginal Expected Shortfall of a bank as the derivative of the market Expected Shortfall with respect to each bank s weight in the market. The main rationale behind the MES with respect to the standard measures of firm-level risk, such as VaR, Beta, Expected Loss, or Volatility, is that they have almost no explanatory power, while beta has only a modest explanatory power, in detecting systemically risky banks (Acharya et al. 2010). Control variables Following prior studies, we include in our models a set of control variables in order to account for bank characteristics, differences in terms of regulation across countries and pre-crisis macroeconomic conditions. A first group of control variables measures differences in bank business structure. One of these control variables is bank size (SIZE), which we measure by the natural log

23 of total bank assets (Pathan, 2009, Peni and Vahamaa, 2012) at the book value. The variable LOANSTA measures differences in banking business model across banks, and it is constructed as the ratio of loans to total assets at book value (de Andres and Vallelado, 2008). It allows us to control for the potential differences between commercial and holding banks. We also add an M&A variable to account for mergers and acquisition over the sample period because they might affect bank governance (Schranz 1993 and Berger et al. 1998). We trace the bank history on Bankscope and identify whether the bank has undergone a major acquisition or merger between 2006 and The M&A variable is a dummy coded 1 if the bank i is involved in an M&A in the analysed year and zero otherwise. Next to these variables, we include a set of variables that are likely to affect risk-taking decisions. In particular, our proxy of bank s liquidity risk is the liquidity ratio (LIQUID) measured by the ratio of liquid assets to customer and short term funding, (LIQUID) that here has to be considered as an inverse measure of the liquidity risk. The impaired loans ratio (IMP, impaired loans/gross loans) takes into account for the banks credit risk, as it can be considered as a proxy of portfolio quality (Casu et al., 2011). We also include Tier 1 as a proxy of bank capitalisation and the leverage (LEV). In particular, following Acharya et al. (2010), we compute the variable LEV as the quasi-market leverage ratio (quasi-market value of assets divided by market value of equity). Together with the MES, the quasi-market leverage is the determinant of a bank systemic risk according to Acharya et al. (2009). Differently from the traditional accounting-based measures of leverage, it also takes into account market conditions and deleveraging decisions. To account for country as source of heterogeneity, we include country dummies in our analyses. We also include year dummies to account for time trend over the sample period. The detailed construction of variables and their expected sign are presented in Table 1, in which we do not include the country and the year dummies.

24 Table 1. Definition of models variables Variable Definition Construction Expected sign MES Marginal Expected Shortfall Dependent variable ES Expected Shortfall Dependent variable VOL Bank returns Annualized standard deviation of bank volatility daily stock returns Dependent variable Ln Z-score Distance to default ROA plus equity-total assets ratio/volatility of ROA Dependent variable Key independent variables BS Board size Number of board of directors H 2: Positive IND Independent Percentage of the independent board directors directors H 1 : Negative BM Frequency of board Number of the meeting held during the meetings fiscal year H 3: Negative CFR Cash flow rights of the largest ultimate Ownership shareholder. CFR equals zero if the bank concentration is widely held (10% cut-off) H 4: Negative Control variables M&A Mergers and Dummy coded 1 if the bank is involved Acquisitions in a M&A in a year and zero otherwise Negative SIZE Bank size Ln of Total assets Positive LOANSTA Bank business activity Loans/ Total assets Negative LEV Quasi-Leverage Quasi-market value of assets / Market value of equity Positive IMP Bank credit risk Impaired loans/ Gross loans Positive TIER 1 Tier 1 Capital ratio Core equity capital / Total risk-weighted Positive LIQUID Bank liquidity position ES y i E( r R VaR ) MES i ES E R R Var i assets Liquid assets/customer and short term funding Negative Notes: This table presents definition, construction, and expected signs on the variables used for the regressions (Model 1). We do not include year and country dummies. However, the country variables do not take into account that there are similarities among the countries in legal and regulatory aspect. Therefore, in an extended model we add a set of variables related to country-level institutional setting and bank regulation. Following Beltratti and Stulz (2012) and Leaven and Levine (2009), we add PRIVATE MONITORING (an index of monitoring on the part of the private sector of the banking system), RESTRICT (an index of regulatory restriction on bank activities of banks) and CAPITAL (index of regulatory oversight of bank capital). We do not include a variable for deposit insurance because the vast majority of the